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21 development machine
1) Техника: короткозабойная врубовая машина, лёгкая врубовая машина, проходческая машина, проходческий комбайн2) Космонавтика: аппарат опытной серии, опытный аппарат3) Автоматика: станок для отработки УП или рабочих режимов, экспериментальный станок -
22 development machine
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23 development machine
экспериментальный станок; станок для отработки УП или рабочих режимовEnglish-Russian dictionary of mechanical engineering and automation > development machine
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24 development machine
komputer programistymaszyna wykorzystywana do budowania oprogramowaniaEnglish-Polish dictionary for engineers > development machine
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25 development machine
komputer programistymaszyna wykorzystywana do budowania oprogramowaniaEnglish-Polish dictionary of Electronics and Computer Science > development machine
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26 Machine Tool Economic Development Committee
Комитет по вопросам экономического развития станкостроения (Великобритания)Англо-русский словарь по экономике и финансам > Machine Tool Economic Development Committee
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27 development machine
проходческая машина; короткозабойная врубовая машинаАнгло-русский словарь по машиностроению > development machine
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28 development machine
Englsh-Russian aviation and space dictionary > development machine
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29 development machine
опытный образец машины или установкиThe English-Russian dictionary on reliability and quality control > development machine
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30 entry-driving machine
English-Russian big polytechnic dictionary > entry-driving machine
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31 magnetic brush development
English-german technical dictionary > magnetic brush development
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32 semi-solid-development
English-german technical dictionary > semi-solid-development
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33 машинное проявление
Большой англо-русский и русско-английский словарь > машинное проявление
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34 машинная обработка
Англо-русский словарь технических терминов > машинная обработка
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35 Howe, Frederick Webster
[br]b. 28 August 1822 Danvers, Massachusetts, USAd. 25 April 1891 Providence, Rhode Island, USA[br]American mechanical engineer, machine-tool designer and inventor.[br]Frederick W.Howe attended local schools until the age of 16 and then entered the machine shop of Gay \& Silver at North Chelmsford, Massachusetts, as an apprentice and remained with that firm for nine years. He then joined Robbins, Kendall \& Lawrence of Windsor, Vermont, as Assistant to Richard S. Lawrence in designing machine tools. A year later (1848) he was made Plant Superintendent. During his time with this firm, Howe designed a profiling machine which was used in all gun shops in the United States: a barrel-drilling and rifling machine, and the first commercially successful milling machine. Robbins \& Lawrence took to the Great Exhibition of 1851 in London, England, a set of rifles built on the interchangeable system. The interest this created resulted in a visit of some members of the British Royal Small Arms Commission to America and subsequently in an order for 150 machine tools, jigs and fixtures from Robbins \& Lawrence, to be installed at the small-arms factory at Enfield. From 1853 to 1856 Howe was in charge of the design and building of these machines. In 1856 he established his own armoury at Newark, New Jersey, but transferred after two years to Middletown, Connecticut, where he continued the manufacture of small arms until the outbreak of the Civil War. He then became Superintendent of the armoury of the Providence Tool Company at Providence, Rhode Island, and served in that capacity until the end of the war. In 1865 he went to Bridgeport, Connecticut, to assist Elias Howe with the manufacture of his sewing machine. After the death of Elias Howe, Frederick Howe returned to Providence to join the Brown \& Sharpe Manufacturing Company. As Superintendent of that establishment he worked with Joseph R. Brown in the development of many of the firm's products, including machinery for the Wilcox \& Gibbs sewing machine then being made by Brown \& Sharpe. From 1876 Howe was in business on his own account as a consulting mechanical engineer and in his later years he was engaged in the development of shoe machinery and in designing a one-finger typewriter, which, however, was never completed. He was granted several patents, mainly in the fields of machine tools and firearms. As a designer, Howe was said to have been a perfectionist, making frequent improvements; when completed, his designs were always sound.[br]Further ReadingJ.W.Roe, 1916, English and American Tool Builders, New Haven; repub. 1926, New York, and 1987, Bradley, 111. (provides biographical details).R.S.Woodbury, 1960, History of the Milling Machine, Cambridge, Mass, (describes Howe's contribution to the development of the milling machine).RTSBiographical history of technology > Howe, Frederick Webster
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The psychology of computer vision. New York: McGrawHill.■ Wittgenstein, L. (1953). Philosophical investigations. Oxford: Basil Blackwell.■ Wittgenstein, L. (1958). The blue and brown books. New York: Harper Colophon.■ Woods, W. A. (1975). What's in a link: Foundations for semantic networks. In D. G. Bobrow & A. Collins (Eds.), Representations and understanding: Studies in cognitive science (pp. 35-84). New York: Academic Press.■ Woodworth, R. S. (1938). Experimental psychology. New York: Holt; London: Methuen (1939).■ Wundt, W. (1904). Principles of physiological psychology (Vol. 1). E. B. Titchener (Trans.). New York: Macmillan.■ Wundt, W. (1907). Lectures on human and animal psychology. J. E. Creighton & E. B. Titchener (Trans.). New York: Macmillan.■ Young, J. Z. (1978). Programs of the brain. New York: Oxford University Press.■ Ziman, J. (1978). Reliable knowledge: An exploration of the grounds for belief in science. Cambridge: Cambridge University Press.Historical dictionary of quotations in cognitive science > Bibliography
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37 tool
1) инструмент; орудие, орудие производства2) резец; инструмент, режущий инструмент; черновой резец ( зубострогального станка)3) приспособление; оснастка4) pl инструментарий; средства; совокупность инструментов6) налаживать ( станок)•to adjust the tool axially — регулировать инструмент в осевом направлении, смещать инструмент в осевом направлении
- 3D modeling toolsto tool roughly — начерно обрабатывать, грубо обрабатывать
- abrading tool
- abrasive tool
- AC-assisted machine tool
- activated tool
- adapter tool
- adjusting tool
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- generating tool
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- hand-guided tool
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- inactive tool
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- infeed slide tool
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- inside turning tool
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- internal boring tool
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- laser tool
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- left-hand tool
- leveling tool
- LH tool
- life-expired tool
- linear mounted tool
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- microsizing tool
- migrating tool
- milling tool
- miniCNC machine tool
- misplaced tool
- mis-set tool
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- modular tool
- mold tool
- molding tool
- monocrystalline diamond tool
- multicavity molding tool
- multifaceted tool
- multifluted tool
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- multiple-impression press tool
- multipoint tool
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- NC machine tool
- NC tool
- negative-rake cutting tool
- noncutting machine tool
- nonrotating tool
- notching press tool
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- OD-turning tool
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- offset tool
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- old tool
- one-sensor-one tool
- operating tool
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- polycrystalline CBN cutting tool
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- powered rotary tool
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- right-angled powered tool
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- rotating tool
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- rough boring tool
- rough cut tool
- roughing tool
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- router tool
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- screw-cutting tool
- screw-rolling tool
- second selection backup tools
- segmented bulging press tool
- self-correcting tool
- shank tool
- shankless cutting tool
- shaped tool
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- shaping tool
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- silicon nitride tool
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- single-tip tool
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- smoothing roller tool
- software development tools
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- solid bit tool
- solid carbide tool
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- SPC tool
- specialized machine tool
- specially outfitted machine tool
- spent tool
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- spinning tool
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- spotting tool
- square cutting tool
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- stamping tool
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- thermal tool
- thread milling tool
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- threaded shank tool
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- throwaway carbide tool
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- to tool up
- touch sensitive tool
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- tube-expanding tool
- Tunruf tool
- turning tool
- turret tool
- ultrasonic tool
- undercutting tool
- underrun tool
- underused tool
- underutilized tool
- undetected broken tool
- unit-type machine tool
- universal boring and thread milling tool
- unmanned machine tool
- untended CNC machine tool
- versatile machine tool
- vibrating tool
- viscous damped tool
- visualization tools
- V-thread tool
- wear-prone tool
- welding laser tool
- wide-finishing tool
- wire-forming tool
- wireless measuring tool
- wobble broach tool
- wood-cutting tool
- workplace tool
- worm-configured tool
- worn cutting tool
- X-axis tool
- Y-axis tool
- Z-axis toolEnglish-Russian dictionary of mechanical engineering and automation > tool
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38 Artificial Intelligence
In my opinion, none of [these programs] does even remote justice to the complexity of human mental processes. Unlike men, "artificially intelligent" programs tend to be single minded, undistractable, and unemotional. (Neisser, 1967, p. 9)Future progress in [artificial intelligence] will depend on the development of both practical and theoretical knowledge.... As regards theoretical knowledge, some have sought a unified theory of artificial intelligence. My view is that artificial intelligence is (or soon will be) an engineering discipline since its primary goal is to build things. (Nilsson, 1971, pp. vii-viii)Most workers in AI [artificial intelligence] research and in related fields confess to a pronounced feeling of disappointment in what has been achieved in the last 25 years. Workers entered the field around 1950, and even around 1960, with high hopes that are very far from being realized in 1972. In no part of the field have the discoveries made so far produced the major impact that was then promised.... In the meantime, claims and predictions regarding the potential results of AI research had been publicized which went even farther than the expectations of the majority of workers in the field, whose embarrassments have been added to by the lamentable failure of such inflated predictions....When able and respected scientists write in letters to the present author that AI, the major goal of computing science, represents "another step in the general process of evolution"; that possibilities in the 1980s include an all-purpose intelligence on a human-scale knowledge base; that awe-inspiring possibilities suggest themselves based on machine intelligence exceeding human intelligence by the year 2000 [one has the right to be skeptical]. (Lighthill, 1972, p. 17)4) Just as Astronomy Succeeded Astrology, the Discovery of Intellectual Processes in Machines Should Lead to a Science, EventuallyJust as astronomy succeeded astrology, following Kepler's discovery of planetary regularities, the discoveries of these many principles in empirical explorations on intellectual processes in machines should lead to a science, eventually. (Minsky & Papert, 1973, p. 11)5) Problems in Machine Intelligence Arise Because Things Obvious to Any Person Are Not Represented in the ProgramMany problems arise in experiments on machine intelligence because things obvious to any person are not represented in any program. One can pull with a string, but one cannot push with one.... Simple facts like these caused serious problems when Charniak attempted to extend Bobrow's "Student" program to more realistic applications, and they have not been faced up to until now. (Minsky & Papert, 1973, p. 77)What do we mean by [a symbolic] "description"? We do not mean to suggest that our descriptions must be made of strings of ordinary language words (although they might be). The simplest kind of description is a structure in which some features of a situation are represented by single ("primitive") symbols, and relations between those features are represented by other symbols-or by other features of the way the description is put together. (Minsky & Papert, 1973, p. 11)[AI is] the use of computer programs and programming techniques to cast light on the principles of intelligence in general and human thought in particular. (Boden, 1977, p. 5)The word you look for and hardly ever see in the early AI literature is the word knowledge. They didn't believe you have to know anything, you could always rework it all.... In fact 1967 is the turning point in my mind when there was enough feeling that the old ideas of general principles had to go.... I came up with an argument for what I called the primacy of expertise, and at the time I called the other guys the generalists. (Moses, quoted in McCorduck, 1979, pp. 228-229)9) Artificial Intelligence Is Psychology in a Particularly Pure and Abstract FormThe basic idea of cognitive science is that intelligent beings are semantic engines-in other words, automatic formal systems with interpretations under which they consistently make sense. We can now see why this includes psychology and artificial intelligence on a more or less equal footing: people and intelligent computers (if and when there are any) turn out to be merely different manifestations of the same underlying phenomenon. Moreover, with universal hardware, any semantic engine can in principle be formally imitated by a computer if only the right program can be found. And that will guarantee semantic imitation as well, since (given the appropriate formal behavior) the semantics is "taking care of itself" anyway. Thus we also see why, from this perspective, artificial intelligence can be regarded as psychology in a particularly pure and abstract form. The same fundamental structures are under investigation, but in AI, all the relevant parameters are under direct experimental control (in the programming), without any messy physiology or ethics to get in the way. (Haugeland, 1981b, p. 31)There are many different kinds of reasoning one might imagine:Formal reasoning involves the syntactic manipulation of data structures to deduce new ones following prespecified rules of inference. Mathematical logic is the archetypical formal representation. Procedural reasoning uses simulation to answer questions and solve problems. When we use a program to answer What is the sum of 3 and 4? it uses, or "runs," a procedural model of arithmetic. Reasoning by analogy seems to be a very natural mode of thought for humans but, so far, difficult to accomplish in AI programs. The idea is that when you ask the question Can robins fly? the system might reason that "robins are like sparrows, and I know that sparrows can fly, so robins probably can fly."Generalization and abstraction are also natural reasoning process for humans that are difficult to pin down well enough to implement in a program. If one knows that Robins have wings, that Sparrows have wings, and that Blue jays have wings, eventually one will believe that All birds have wings. This capability may be at the core of most human learning, but it has not yet become a useful technique in AI.... Meta- level reasoning is demonstrated by the way one answers the question What is Paul Newman's telephone number? You might reason that "if I knew Paul Newman's number, I would know that I knew it, because it is a notable fact." This involves using "knowledge about what you know," in particular, about the extent of your knowledge and about the importance of certain facts. Recent research in psychology and AI indicates that meta-level reasoning may play a central role in human cognitive processing. (Barr & Feigenbaum, 1981, pp. 146-147)Suffice it to say that programs already exist that can do things-or, at the very least, appear to be beginning to do things-which ill-informed critics have asserted a priori to be impossible. Examples include: perceiving in a holistic as opposed to an atomistic way; using language creatively; translating sensibly from one language to another by way of a language-neutral semantic representation; planning acts in a broad and sketchy fashion, the details being decided only in execution; distinguishing between different species of emotional reaction according to the psychological context of the subject. (Boden, 1981, p. 33)Can the synthesis of Man and Machine ever be stable, or will the purely organic component become such a hindrance that it has to be discarded? If this eventually happens-and I have... good reasons for thinking that it must-we have nothing to regret and certainly nothing to fear. (Clarke, 1984, p. 243)The thesis of GOFAI... is not that the processes underlying intelligence can be described symbolically... but that they are symbolic. (Haugeland, 1985, p. 113)14) Artificial Intelligence Provides a Useful Approach to Psychological and Psychiatric Theory FormationIt is all very well formulating psychological and psychiatric theories verbally but, when using natural language (even technical jargon), it is difficult to recognise when a theory is complete; oversights are all too easily made, gaps too readily left. This is a point which is generally recognised to be true and it is for precisely this reason that the behavioural sciences attempt to follow the natural sciences in using "classical" mathematics as a more rigorous descriptive language. However, it is an unfortunate fact that, with a few notable exceptions, there has been a marked lack of success in this application. It is my belief that a different approach-a different mathematics-is needed, and that AI provides just this approach. (Hand, quoted in Hand, 1985, pp. 6-7)We might distinguish among four kinds of AI.Research of this kind involves building and programming computers to perform tasks which, to paraphrase Marvin Minsky, would require intelligence if they were done by us. Researchers in nonpsychological AI make no claims whatsoever about the psychological realism of their programs or the devices they build, that is, about whether or not computers perform tasks as humans do.Research here is guided by the view that the computer is a useful tool in the study of mind. In particular, we can write computer programs or build devices that simulate alleged psychological processes in humans and then test our predictions about how the alleged processes work. We can weave these programs and devices together with other programs and devices that simulate different alleged mental processes and thereby test the degree to which the AI system as a whole simulates human mentality. According to weak psychological AI, working with computer models is a way of refining and testing hypotheses about processes that are allegedly realized in human minds.... According to this view, our minds are computers and therefore can be duplicated by other computers. Sherry Turkle writes that the "real ambition is of mythic proportions, making a general purpose intelligence, a mind." (Turkle, 1984, p. 240) The authors of a major text announce that "the ultimate goal of AI research is to build a person or, more humbly, an animal." (Charniak & McDermott, 1985, p. 7)Research in this field, like strong psychological AI, takes seriously the functionalist view that mentality can be realized in many different types of physical devices. Suprapsychological AI, however, accuses strong psychological AI of being chauvinisticof being only interested in human intelligence! Suprapsychological AI claims to be interested in all the conceivable ways intelligence can be realized. (Flanagan, 1991, pp. 241-242)16) Determination of Relevance of Rules in Particular ContextsEven if the [rules] were stored in a context-free form the computer still couldn't use them. To do that the computer requires rules enabling it to draw on just those [ rules] which are relevant in each particular context. Determination of relevance will have to be based on further facts and rules, but the question will again arise as to which facts and rules are relevant for making each particular determination. One could always invoke further facts and rules to answer this question, but of course these must be only the relevant ones. And so it goes. It seems that AI workers will never be able to get started here unless they can settle the problem of relevance beforehand by cataloguing types of context and listing just those facts which are relevant in each. (Dreyfus & Dreyfus, 1986, p. 80)Perhaps the single most important idea to artificial intelligence is that there is no fundamental difference between form and content, that meaning can be captured in a set of symbols such as a semantic net. (G. Johnson, 1986, p. 250)Artificial intelligence is based on the assumption that the mind can be described as some kind of formal system manipulating symbols that stand for things in the world. Thus it doesn't matter what the brain is made of, or what it uses for tokens in the great game of thinking. Using an equivalent set of tokens and rules, we can do thinking with a digital computer, just as we can play chess using cups, salt and pepper shakers, knives, forks, and spoons. Using the right software, one system (the mind) can be mapped into the other (the computer). (G. Johnson, 1986, p. 250)19) A Statement of the Primary and Secondary Purposes of Artificial IntelligenceThe primary goal of Artificial Intelligence is to make machines smarter.The secondary goals of Artificial Intelligence are to understand what intelligence is (the Nobel laureate purpose) and to make machines more useful (the entrepreneurial purpose). (Winston, 1987, p. 1)The theoretical ideas of older branches of engineering are captured in the language of mathematics. We contend that mathematical logic provides the basis for theory in AI. Although many computer scientists already count logic as fundamental to computer science in general, we put forward an even stronger form of the logic-is-important argument....AI deals mainly with the problem of representing and using declarative (as opposed to procedural) knowledge. Declarative knowledge is the kind that is expressed as sentences, and AI needs a language in which to state these sentences. Because the languages in which this knowledge usually is originally captured (natural languages such as English) are not suitable for computer representations, some other language with the appropriate properties must be used. It turns out, we think, that the appropriate properties include at least those that have been uppermost in the minds of logicians in their development of logical languages such as the predicate calculus. Thus, we think that any language for expressing knowledge in AI systems must be at least as expressive as the first-order predicate calculus. (Genesereth & Nilsson, 1987, p. viii)21) Perceptual Structures Can Be Represented as Lists of Elementary PropositionsIn artificial intelligence studies, perceptual structures are represented as assemblages of description lists, the elementary components of which are propositions asserting that certain relations hold among elements. (Chase & Simon, 1988, p. 490)Artificial intelligence (AI) is sometimes defined as the study of how to build and/or program computers to enable them to do the sorts of things that minds can do. Some of these things are commonly regarded as requiring intelligence: offering a medical diagnosis and/or prescription, giving legal or scientific advice, proving theorems in logic or mathematics. Others are not, because they can be done by all normal adults irrespective of educational background (and sometimes by non-human animals too), and typically involve no conscious control: seeing things in sunlight and shadows, finding a path through cluttered terrain, fitting pegs into holes, speaking one's own native tongue, and using one's common sense. Because it covers AI research dealing with both these classes of mental capacity, this definition is preferable to one describing AI as making computers do "things that would require intelligence if done by people." However, it presupposes that computers could do what minds can do, that they might really diagnose, advise, infer, and understand. One could avoid this problematic assumption (and also side-step questions about whether computers do things in the same way as we do) by defining AI instead as "the development of computers whose observable performance has features which in humans we would attribute to mental processes." This bland characterization would be acceptable to some AI workers, especially amongst those focusing on the production of technological tools for commercial purposes. But many others would favour a more controversial definition, seeing AI as the science of intelligence in general-or, more accurately, as the intellectual core of cognitive science. As such, its goal is to provide a systematic theory that can explain (and perhaps enable us to replicate) both the general categories of intentionality and the diverse psychological capacities grounded in them. (Boden, 1990b, pp. 1-2)Because the ability to store data somewhat corresponds to what we call memory in human beings, and because the ability to follow logical procedures somewhat corresponds to what we call reasoning in human beings, many members of the cult have concluded that what computers do somewhat corresponds to what we call thinking. It is no great difficulty to persuade the general public of that conclusion since computers process data very fast in small spaces well below the level of visibility; they do not look like other machines when they are at work. They seem to be running along as smoothly and silently as the brain does when it remembers and reasons and thinks. On the other hand, those who design and build computers know exactly how the machines are working down in the hidden depths of their semiconductors. Computers can be taken apart, scrutinized, and put back together. Their activities can be tracked, analyzed, measured, and thus clearly understood-which is far from possible with the brain. This gives rise to the tempting assumption on the part of the builders and designers that computers can tell us something about brains, indeed, that the computer can serve as a model of the mind, which then comes to be seen as some manner of information processing machine, and possibly not as good at the job as the machine. (Roszak, 1994, pp. xiv-xv)The inner workings of the human mind are far more intricate than the most complicated systems of modern technology. Researchers in the field of artificial intelligence have been attempting to develop programs that will enable computers to display intelligent behavior. Although this field has been an active one for more than thirty-five years and has had many notable successes, AI researchers still do not know how to create a program that matches human intelligence. No existing program can recall facts, solve problems, reason, learn, and process language with human facility. This lack of success has occurred not because computers are inferior to human brains but rather because we do not yet know in sufficient detail how intelligence is organized in the brain. (Anderson, 1995, p. 2)Historical dictionary of quotations in cognitive science > Artificial Intelligence
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39 Meikle, Andrew
SUBJECT AREA: Agricultural and food technology[br]b. 1719 Scotlandd. 27 November 1811[br]Scottish millwright and inventor of the threshing machine.[br]The son of the millwright James Meikle, who is credited with the introduction of the winnowing machine into Britain, Andrew Meikle followed in his father's footsteps. His inventive inclinations were first turned to developing his father's idea, and together with his own son George he built and patented a double-fan winnowing machine.However, in the history of agricultural development Andrew Meikle is most famous for his invention of the threshing machine, patented in 1784. He had been presented with a model of a threshing mill designed by a Mr Ilderton of Northumberland, but after failing to make a full-scale machine work, he developed the concept further. He eventually built the first working threshing machine for a farmer called Stein at Kilbagio. The patent revolutionized farming practice because it displaced the back-breaking and soul-destroying labour of flailing the grain from the straw. The invention was of great value in Scotland and in northern England when the land was becoming underpopulated as a result of heavy industrialization, but it was bitterly opposed in the south of England until well into the nineteenth century. Although the introduction of the threshing machine led to the "Captain Swing" riots of the 1830s, in opposition to it, it shortly became universal.Meikle's provisional patent in 1785 was a natural progression of earlier attempts by other millwrights to produce such a machine. The published patent is based on power provided by a horse engine, but these threshing machines were often driven by water-wheels or even by windmills. The corn stalks were introduced into the machine where they were fed between cast-iron rollers moving quite fast against each other to beat the grain out of the ears. The power source, whether animal, water or wind, had to cause the rollers to rotate at high speed to knock the grain out of the ears. While Meikle's machine was at first designed as a fixed barn machine powered by a water-wheel or by a horse wheel, later threshing machines became mobile and were part of the rig of an agricultural contractor.In 1788 Meikle was awarded a patent for the invention of shuttered sails for windmills. This patent is part of the general description of the threshing machine, and whilst it was a practical application, it was superseded by the work of Thomas Cubitt.At the turn of the century Meikle became a manufacturer of threshing machines, building appliances that combined the threshing and winnowing principles as well as the reciprocating "straw walkers" found in subsequent threshing machines and in conventional combine harvesters to the present day. However, he made little financial gain from his invention, and a public subscription organized by the President of the Board of Agriculture, Sir John Sinclair, raised £1,500 to support him towards the end of his life.[br]Bibliography1831, Threshing Machines in The Dictionary of Mechanical Sciences, Arts and Manufactures, London: Jamieson, Alexander.7 March 1768, British patent no. 896, "Machine for dressing wheat, malt and other grain and for cleaning them from sand, dust and smut".9 April 1788, British patent no. 1,645, "Machine which may be worked by cattle, wind, water or other power for the purpose of separating corn from the straw".Further ReadingJ.E.Handley, 1953, Scottish Farming in the 18th Century, and 1963, The Agricultural Revolution in Scotland (both place Meikle and his invention within their context).G.Quick and W.Buchele, 1978, The Grain Harvesters, American Society of Agricultural Engineers (gives an account of the early development of harvesting and cereal treatment machinery).KM / AP -
40 Howe, Elias
[br]b. 9 July 1819 Spencer, Massachusetts, USAd. 3 October 1867 Bridgeport, Connecticut, USA[br]American inventor of one of the earliest successful sewing machines.[br]Son of Elias Howe, a farmer, he acquired his mechanical knowledge in his father's mill. He left school at 12 years of age and was apprenticed for two years in a machine shop in Lowell, Massachusetts, and later to an instrument maker, Ari Davis in Boston, Massachusetts, where his master's services were much in demand by Harvard University. Fired by a desire to invent a sewing machine, he utilized the experience gained in Lowell to devise a shuttle carrying a lower thread and a needle carrying an upper thread to make lock-stitch in straight lines. His attempts were so rewarding that he left his job and was sustained first by his father and then by a partner. By 1845 he had built a machine that worked at 250 stitches per minute, and the following year he patented an improved machine. The invention of the sewing machine had an enormous impact on the textile industry, stimulating demand for cloth because making up garments became so much quicker. The sewing machine was one of the first mass-produced consumer durables and was essentially an American invention. William Thomas, a London manufacturer of shoes, umbrellas and corsets, secured the British rights and persuaded Howe to come to England to apply it to the making of shoes. This Howe did, but he quarrelled with Thomas after less than one year. He returned to America to face with his partner, G.W.Bliss, a bigger fight over his patent (see I.M. Singer), which was being widely infringed. Not until 1854 was the case settled in his favour. This litigation threatened the very existence of the new industry, but the Great Sewing Machine Combination, the first important patent-pooling arrangement in American history, changed all this. For a fee of $5 on every domestically-sold machine and $1 on every exported one, Howe contributed to the pool his patent of 1846 for a grooved eye-pointed needle used in conjunction with a lock-stitch-forming shuttle. Howe's patent was renewed in 1861; he organized and equipped a regiment during the Civil War with the royalties. When the war ended he founded the Howe Machine Company of Bridgeport, Connecticut.[br]Further ReadingObituary, 1867, Engineer 24.Obituary, 1867, Practical Magazine 5.F.G.Harrison, 1892–3, Biographical Sketches of Pre-eminent Americans (provides a good account of Howe's life and achievements).N.Salmon, 1863, History of the Sewing Machine from the Year 1750, with a biography of Elias Howe, London (tells the history of sewing machines).F.B.Jewell, 1975, Veteran Sewing Machines, A Collector's Guide, Newton Abbot (a more modern account of the history of sewing machines).C.Singer (ed.), 1958, A History of Technology, Vol. V, Oxford: Clarendon Press (covers the mechanical developments).D.A.Hounshell, 1984, From the American System to Mass Production 1800–1932. TheDevelopment of Manufacturing Technology in the United States, Baltimore (examines the role of the American sewing machine companies in the development of mass-production techniques).RLH
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